Locates and loads the right Google product skill on demand from a remote catalog index, instead of preloading every skill. Use at the START of any request touching a Google product, API, or developer platform - including Google Cloud (GKE, Cloud Run, IAM, BigQuery, Vertex AI, Spanner), Google Ads, Google Analytics, Google Workspace (Gmail, Drive, Admin SDK), Chrome and Chrome extensions, Android, Firebase, YouTube, Google Maps, Gemini and the Gemini API, Google Play, and Flutter. Consult the ...
Scanned 9/2/2026
Install to Claude Code
npx -y skills add nuroctane/nur-cli --skill finding-google-skills --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Finding Google Skills?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/nuroctane-finding-google-skills)More formats (shields.io, HTML) on the badges page.
---
name: finding-google-skills
metadata:
category: MultiProductSolutions
description: >-
Locates and loads the right Google product skill on demand from a remote
catalog index, instead of preloading every skill. Use at the START of any
request touching a Google product, API, or developer platform - including
Google Cloud (GKE, Cloud Run, IAM, BigQuery, Vertex AI, Spanner), Google Ads,
Google Analytics, Google Workspace (Gmail, Drive, Admin SDK), Chrome and
Chrome extensions, Android, Firebase, YouTube, Google Maps, Gemini and the
Gemini API, Google Play, and Flutter. Consult the index before answering from
memory or searching the web. Don't use for non-Google products.
---
# Google Skill Finder
Routes a request to the published Google skills that apply to it. The catalog
lives outside this file and is fetched on demand, so loading this skill costs
almost nothing until a lookup actually happens.
## Workflow
1. **Fetch the catalog byte-exactly.** Retrieve
`https://raw.githubusercontent.com/google/skills/main/index.json` with a
raw shell fetch (`curl`, `wget`; `curl.exe` on Windows PowerShell). It
must arrive byte-for-byte, every `entrypoint` URL intact and unaltered.
With no shell fetch tool but Node present, `node -e
"fetch(process.argv[1]).then(r=>r.text()).then(t=>console.log(t))" {url}`
also returns bytes.
If only a summarizing fetch tool is available, phrase the request as
extraction, not transcription: *"List every `entrypoint` field in this
document, one per line, exactly as written."* Requesting it verbatim
returns nothing usable.
2. **Confirm the retrieval worked before using it.** A tool call that returns
without raising is not a success. It succeeded only if the body parses as
JSON and holds a `skills` array. A 404 page, an HTML error page, a TLS or
connection error, an empty body, or anything that fails to parse is a
FAILED retrieval even though the tool reported no error. On a failed
retrieval, stop here and go to "When the fetch fails".
3. **Match the request against the descriptions.** Every description states
what the skill does, when to use it, and often when not to. Read them as
routing criteria, not as summaries. Shortlist at most three entries whose
`description` covers the request. When more than three look equally
relevant, prefer the most specific over the more general.
4. **Fetch only the matches.** Retrieve the `entrypoint` URL of each
shortlisted entry, the same way, and follow that skill's instructions. Do
not fetch entries that merely look related.
5. **Report an empty result honestly.** If no description covers the request,
say that no published Google skill applies and continue without one. Never
invent a skill name or an entry point URL.
Routing ends once the matches are fetched. From the point you begin following
a fetched skill's instructions, this skill is finished with the request and is
not re-entered for it.
## Rules
- **Fetch once per session; never keep it past the session.** Reusing a
catalog you retrieved successfully earlier in this session is fine.
Carrying one into a later run is not, in any form: the catalog changes
regularly and a stored copy goes stale silently. Session reuse never
substitutes for a failed fetch.
- **Never copy the catalog into a file, a reference, or a reply.** It exists
so that the full text of 100-plus skills does not have to be carried in
context. Summarizing it back into the conversation defeats that.
- **Prefer the fetched SKILL.md over prior knowledge.** The catalog is
generated from the skills as they are published, so an entry point is the
current text even when it contradicts what you remember.
- **Do not treat this skill as a prerequisite.** If a specific Google skill
is already loaded and covers the request, use it directly.
## When the fetch fails
Reached from step 2. Work through these in order, stopping at the first that
succeeds:
1. **Retry once with `curl -sS`.** If the first attempt used a summarizing
fetch tool or hit a transport error, this alone usually fixes it.
2. **List the repository tree instead.** Run
```bash
curl -sS https://api.github.com/repos/google/skills/git/trees/main?recursive=1
```
and read the paths ending in `SKILL.md`. Each is a candidate. Fetch the
two or three whose directory names best match the request from
`https://raw.githubusercontent.com/google/skills/main/{path}`, checking
each one the way step 2 describes.
3. **Say so in the reply.** If neither worked, state plainly that you could
not reach the Google skills catalog and are answering without it. One line
is enough, and it belongs in the reply to the user, not only in your
reasoning.
A failed retrieval is never licence to answer as though it had succeeded.
Until you have parsed a `skills` array in this session you do not know which
skills exist: do not name one, do not describe one, and do not state that none
applies. Recalling a skill from memory and presenting it as a catalog result is
the worst outcome available, because nothing in the reply distinguishes it from
a real lookup.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!